A Neural Network Applied to Sensor Signal Processing: Determination of Copper in Water

A neural network is applied to sensor signal processing in a novel ap proach to the determination of copper in reservoir water. The neural network performed well in determining the correct total of copper concentration in water when provided with only pH and copper(II) ion-selective electrode experi...

Full description

Saved in:
Bibliographic Details
Published in:Journal of intelligent material systems and structures 1992-07, Vol.3 (3), p.418-431
Main Authors: Sperring, D.A., Chow, C.W., Mulcahy, D.E., Davey, D.E., Haskard, M.R.
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Copper
Exact sciences and technology
Ion selective electrodes
Mathematical models
Metrology, automation
Neural networks
PH sensors
Signal processing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A neural network is applied to sensor signal processing in a novel ap proach to the determination of copper in reservoir water. The neural network performed well in determining the correct total of copper concentration in water when provided with only pH and copper(II) ion-selective electrode experimental data. This task followed an initial period of network exposure to a set of experimental data triplets, which were used as examples of the required input/output data mapping.
ISSN:1045-389X
1530-8138
DOI:10.1177/1045389X9200300303